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triage-failures

Diagnose failed AI simulation runs by checking statuses, errors, and conversation artifacts.

Updated May 5, 2026
Search Tags:#debugging#simulation#diagnostics#error analysis#AI testing
One-click install
npx skills add https://github.com/AratoAi/claude-code-plugin --skill triage-failures-aratoai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: triage-failures
Source: https://github.com/AratoAi/claude-code-plugin/tree/main/skills/triage-failures
Command: npx skills add https://github.com/AratoAi/claude-code-plugin --skill triage-failures-aratoai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill enables users to identify the causes of failed or problematic AI simulation runs, reducing downtime and improving debugging efficiency.

Core Features & Use Cases

  • Run Status Diagnosis: Check the current status of simulation runs and identify whether they are ongoing, failed, or completed with issues.
  • Detailed Error Analysis: Retrieve error messages, run details, and find root causes such as connectivity or authentication problems.
  • Interview Artifacts: Access screenshots and transcripts of failed conversations to visually identify issues like UI errors or unexpected prompts.
  • Use Case: A QA engineer wants to quickly determine why a test run failed and gather insights from conversation logs to fix the underlying issue.

Quick Start

Ask the system to check the status of a specific run and review associated assets to diagnose the failure.

Frequently Asked Questions about triage-failures

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I debug failed AI simulation runs and find the root cause?▼

To debug failed AI simulation runs, diagnose run statuses, retrieve error messages, and review conversation artifacts to identify root causes like connectivity or authentication problems efficiently.

What is the best way to check AI testing run statuses and error messages?▼

Checking AI testing run statuses involves verifying whether runs are ongoing, failed, or completed with issues, then retrieving detailed error messages to pinpoint the exact failure point for troubleshooting.

Can I use conversation transcripts and screenshots to diagnose simulation failures?▼

Yes, you can access interview artifacts like screenshots and transcripts from failed conversations to visually diagnose simulation failures, identifying UI errors or unexpected prompts within the testing workflow.

Does this diagnostics approach work with various simulation run states?▼

Yes, this diagnostics approach ensures compatibility with various run states, allowing you to check ongoing, failed, or completed runs with issues to gather detailed insights for troubleshooting.

Why does my AI simulation run keep failing with interface issues?▼

AI simulation runs failing with interface issues can be diagnosed by retrieving run details and checking conversation artifacts to visually identify UI errors, unexpected prompts, or authentication problems.

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